
We develop a linear parameter-varying (LPV) spectral decomposition method, based on least-squares estimation and kernel expansions. Statistical properties of the estimator are analyzed and verified in simulations. The method is linear in the parameters, applicable to both the analysis and modeling problems and is demonstrated on both simulated signals as well as measurements of the torque in an electrical motor.
Signal Processing, Spectral Estimation, System Identification, LPV-modeling, Spectral Decomposition
Signal Processing, Spectral Estimation, System Identification, LPV-modeling, Spectral Decomposition
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